List of Sejm members (2011–15)
The seventh term of the Government of the Republic of Poland is the term of the Government that ran from 8 November 2011 to 11 November 2015.[1]
 |
|---|
| This article is part of a series on the politics and government of Poland |
|
|
Related topics
|
 |
Officers
| Name | Party | Notes | ||
|---|---|---|---|---|
| Senior Marshal | Józef Zych | Polish People's Party | ||
| Marshal | Ewa Kopacz | Civic Platform | Served from 8 November 2011 to 22 September 2014 | |
| Marshal | Radosław Sikorski | Civic Platform | Served from 24 September 2014 to 23 June 2015 | |
| Marshal | Małgorzata Kidawa-Błońska | Civic Platform | Served from 25 June 2015 to 11 November 2015 | |
| Deputy Marshals | Cezary Grabarczyk | Civic Platform | ||
| Eugeniusz Grzeszczak | Polish People's Party | |||
| Marek Kuchciński | Law and Justice | |||
| Wanda Nowicka | Non-attached member | |||
| Jerzy Wenderlich | Democratic Left Alliance | |||
| Elżbieta Radziszewska | Civic Platform | |||
Members of Sejm
gollark: Instead of recomputing the embeddings every time a new sentence comes in.
gollark: The embeddings for your example sentences are the same each time you run the model, so you can just store them somewhere and run the cosine similarity thing on all of them in bulk.
gollark: Well, it doesn't look like you ever actually move the `roberta-large-mnli` model to your GPU, but I think the Sentence Transformers one is slow because you're using it wrong.
gollark: For the sentence_transformers one, are you precomputing the embeddings for the example sentences *then* just cosine-similaritying them against the new sentence? Because if not that's probably a very large bottleneck.
gollark: sentence_transformers says you should be able to do several thousand sentences a second on a V100, which I'm pretty sure is worse than your GPU. Are you actually running it on the GPU?
See also
- 2011 Polish parliamentary election
- List of Polish senators (2011–15)
- List of Sejm members (2007–11) - former term
References
| | |
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.